多智能体协作生成高质量长时音乐，提升可控性与可编辑性。
CoComposer: LLM Multi-agent Collaborative Music Composition
- 五个智能体分工协作，模拟传统作曲流程
- 在四项评估标准中均优于现有系统，且支持复杂作品生成
- 适合音乐创作、交互式作曲与可解释生成场景
现有AI音乐生成工具在生成时长、音乐质量与可控性方面存在局限。本文提出CoComposer，一个由五个协作智能体组成的多智能体系统，每个智能体基于传统作曲流程承担特定任务。通过AudioBox-Aesthetics系统，我们在四个作曲维度上对CoComposer进行实验评估。测试使用GPT-4o、DeepSeek-V3-0324与Gemini-2.5-Flash三个LLM，结果表明：(1) CoComposer在音乐质量上优于现有基于LLM的多智能体系统；(2) 相较于单智能体系统，其在生产复杂度上表现更优。相较于非LLM的MusicLM，CoComposer具有更好的可解释性与可编辑性，尽管MusicLM在音乐生成质量上仍略胜一筹。
原文摘要 · Abstract (English)
Existing AI Music composition tools are limited in generation duration, musical quality, and controllability. We introduce CoComposer, a multi-agent system that consists of five collaborating agents, each with a task based on the traditional music composition workflow. Using the AudioBox-Aesthetics system, we experimentally evaluate CoComposer on four compositional criteria. We test with three LLMs (GPT-4o, DeepSeek-V3-0324, Gemini-2.5-Flash), and find (1) that CoComposer outperforms existing multi-agent LLM-based systems in music quality, and (2) compared to a single-agent system, in production complexity. Compared to non- LLM MusicLM, CoComposer has better interpretability and editability, although MusicLM still produces better music.
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